A consumer's credential information, such as indicators of financial responsibility, financial capacity, financial affluence, financial risk, etc., affect what products or services a consumer is likely to purchase, and this in turn affects what offers the merchant should offer in the first place. For instance, a consumer with low financial risk and high financial affluence credentials would be more willing to consider a more expensive set of products than would a consumer with high debt and little ability to pay for the products or services. Merchants, particularly online merchants, are limited in their ability to make personalized, real-time offers to specific groups of consumers. This limitation arises from the fact that merchants usually cannot ascertain financial credential information relating to the consumer until after a transaction is complete.
When a consumer visits a merchant's website, e.g., amazon.com, that merchant cannot ascertain credential information relating to the consumer and thus, the merchant is unable to distinguish the financial capacity of one consumer from the financial capacity of another consumer. As a result, online merchants must provide the same product or service offerings to every consumer, regardless of the financial status of that consumer.
Currently, an online merchant must infer from information, such as the web sites recently visited by the consumer (e.g., as determined by cookies placed on the computer) or demographic information provided by the consumer, and the like, to predict what a consumer's financial credentials might be. As a result, an online merchant is forced to infer that a consumer has a given purchase capacity. In any event, this methodology is somewhat unreliable because the information associated with the consumer is not validated. For example, the consumer could provide false demographic or financial information in response to a question. This mechanism is especially inaccurate when more that one individual uses the computer within a household. This presents a less than ideal method of effectively targeting preferred consumer groups.
By way of analogy, suppose a potential buyer visits a car dealership. The car salesperson, by observation, determines that the potential buyer holds title to a very expensive car. By observing the potential buyer's title to the car, the salesperson is able to view validated information that provides an indication of that consumer's purchasing capacity. Accordingly, the salesperson can make decisions as to the likelihood that that particular purchaser will potentially buy one car over another. Thus the sales pitch and sales offers can be tailored to the individual consumer. In this example, the salesperson would be motivated to make personalized offers to preferred consumers based upon a perception the salesperson has of the customer. That is, the potential buyer's car is an indication of that buyer's financial capacity. Given this information, the car salesperson increases the likelihood of acquiring a preferred customer while reducing the likelihood of acquiring a less profitable customer, or even worse, wasting time dealing with a consumer that will not financially qualify to make a purchase in the first place.
The situation described above does not readily apply to the virtual world of on-line shopping. That is, online merchants cannot readily ascertain validated credential information relating to consumers visiting its website. As such, an online merchant must provide the same offers and present the same merchandise or service to every potential consumer.